A Systems Approach to Climate, Water and Diarrhea in Hubli-Dharward, India

Tuesday, 16 December 2014: 5:00 PM
Jonathan Edward Mellor and Julie Zimmerman, Yale University, New Haven, CT, United States
Although evidence suggests that climate change will negatively impact water resources and hence diarrheal disease rates in the developing world, there is uncertainty surrounding prior studies. This is due to the complexity of the pathways by which climate impacts diarrhea rates making it difficult to develop interventions. Therefore, our goal was to develop a mechanistic systems approach that incorporates the complex climate, human, engineered and water systems to relate climate change to diarrhea rates under future climate scenarios.

To do this, we developed an agent-based model (ABM). Our agents are households and children living in Hubli-Dharward, India. The model was informed with 15 months of weather, water quality, ethnographic and diarrhea incidence data. The model's front end is a stochastic weather simulator incorporating 15 global climate models to simulate rainfall and temperature. The water quality available to agents (residents) on a model "day" is a function of the simulated day's weather and is fully validated with field data. As with the field data, as the ambient temperature increases or it rains, the quality of water available to residents in the model deteriorates. The propensity for an resident to get diarrhea is calculated with an integrated Quantitative Microbial Risk Assessment model with uncertainty simulated with a bootstrap method. Other factors include hand-washing, improved water sources, household water treatment and improved sanitation.

The benefits of our approach are as follows:

  • Our mechanistic method allows us to develop scientifically derived adaptation strategies.
  • We can quantitatively link climate scenarios with diarrhea incidence over long time periods.
  • We can explore the complex climate and water system dynamics, rank risk factor importance, examine a broad range of scenarios and identify tipping points.
  • Our approach is modular and expandable such that new datasets can be integrated to study climate impacts on a larger scale.

Our results indicate that climate change will have a serious effect on diarrhea incidence in the region. However, adaptation strategies including more reliable water supplies and household water treatment can mitigate these impacts.